Latent class growth mixture modeling of HbA1C trajectories identifies individuals at high risk of developing complications of type 2 diabetes mellitus in the UK Biobank
Authors' conclusion
Individuals with T2D who show higher and more variable HbA1c trajectories are at increased risk of developing T2D-related complications. Early identification of patients at risk, based on factors such as age at diagnosis and previous healthcare utilization could improve patient outcomes.
Study context
- Population
- Unrelated individuals of European ancestry with T2D, UK Biobank; Hemoglobin A1c (HbA1c) trajectories over 10 years after T2D diagnosis
- Participants
- 12,435 individuals
- Exposure
- Five higher/more variable HbA1c trajectory classes vs low and stable class
- Outcome
- Distinct long-term HbA1c trajectory classes and their association with health-related traits and T2D complications
- Follow-up
- 10 years following T2D diagnosis
Methodological detailslatent class growth mixture modeling, UK Biobank linked to primary care records
- Latent class growth mixture modeling
- UK Biobank linked to primary care records
Main finding
As reported in the abstract
Five smaller classes vs Low and stableHazard ratio (CI)
Stroke
1.55(1.31–1.84)
Kidney disease
1.39(1.27–1.53)
All-cause mortality
1.36(1.23–1.51)
Progression to combination therapy
3.22(3.04–3.41)
Progression to insulin
3.21(2.89–3.55)
- HbA1c trajectory classes identified
- 6
- Largest class (low and stable HbA1c)
- 76.8%
Observational data: associations, not effects.
Further findings
Characteristics of the five smaller classes
- Associated with younger age at T2D diagnosis, higher fasting and random glucose, higher BMI polygenic score and increased healthcare use before T2D diagnosis
Original publication
Latent class growth mixture modeling of HbA1C trajectories identifies individuals at high risk of developing complications of type 2 diabetes mellitus in the UK Biobank. BMJ Open Diabetes Res Care. Published 8 September 2025. doi:10.
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